Maintaining Symmetry between Convolutional Neural Network Accuracy and Performance on an Edge TPU with a Focus on Transfer Learning Adjustments
Transfer learning has proven to be a valuable technique for deploying machine learning
models on edge devices and embedded systems. By leveraging pre-trained models and fine …
models on edge devices and embedded systems. By leveraging pre-trained models and fine …
Output-directed dynamic quantization for DNN acceleration
Quantization is an effective technique for reducing the number of computations and
improving the performance of deep neural networks (DNNs). Weight quantization is popular …
improving the performance of deep neural networks (DNNs). Weight quantization is popular …